Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy

In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.     

博客技术在高校教育信息化中的应用

在信息时代和知识经济社会,可以说与他人进行经常性的沟通以及共享资源已成为一种日益重要的趋势。对高等院校从事本科教学的教师而言,博客的兴起和广泛应用为他们提供了此种便利。而对教育信息化而言,博客无疑又成为了一个难得的载体,在学校条件并不成熟时使对课程教学的知识管理成为可能,更为教学课堂内外的资源共事和人与人之间沟通和交流搭建了一个良好的平台,因此进一步研究博客对促进高校本科信息化教学无疑具有现实重要意义。     

The effectiveness of Web search engines for retrieving relevant ecommerce links

Ecommerce is developing into a fast-growing channel for new business, so a strong presence in this domain could prove essential to the success of numerous commercial organizations. However, there is little research examining ecommerce at the individual customer level, particularly on the success of everyday ecommerce searches. This is critical for the continued success of online commerce. The purpose of this research is to evaluate the effectiveness of search engines in the retrieval of relevant ecommerce links. The study examines the effectiveness of five different types of search engines in response to ecommerce queries by comparing the engines’ quality of ecommerce links using topical relevancy ratings. This research employs 100 ecommerce queries, five major search engines, and more than 3540 Web links. The findings indicate that links retrieved using an ecommerce search engine are significantly better than those obtained from most other engines types but do not significantly differ from links obtained from a Web directory service. We discuss the implications for Web system design and ecommerce marketing campaigns.     

基于顶级本体语义表达的领域本体构建实证研究

以清晰表达知识内涵、促进信息资源语义共享为目的,以卫生监督调查信息为研究案例,尝试利用顶级本体属性元素构建具有通用语义特征的领域本体。通过领域知识本体的构建实证,详尽阐述依托“七步法”构筑领域本体的方法,探讨使用领域术语构建本体知识表达的途径,实现了卫生监督调查信息知识的本体化,为该领域知识的信息资源语义整合提供研究基础。     

Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing

Social tagging systems enable users to assign arbitrary tags to various digital resources. However, they face vague-meaning problems when users retrieve or present resources with the keyword-based tags. In order to solve these problems, this study takes advantage of Semantic Web technology and the topological characteristics of knowledge maps to develop a system that comprises a semantic tagging mechanism and triple-pattern and visual searching mechanisms. A field experiment was conducted to evaluate the effectiveness and user acceptance of these mechanisms in a knowledge sharing context. The results show that the semantic social tagging system is more effective than a keyword-based system. The visualized knowledge map helps users capture an overview of the knowledge domain, reduce cognitive effort for the search, and obtain more enjoyment. Traditional keyword tagging with a keyword search still has the advantage of ease of use and the users had higher intention to use it. This study also proposes directions for future development of semantic social tagging systems.     

基于学科博客的学科服务应用探讨

文章首先对如何应用博客的核心技术(Tag、Track-back、RSS)进行学科资源建设和学科知识服务进行探索;然后选择若干"211工程"高校图书馆,对其学科博客开展和应用现状进行调研,调研发现:自建博客平台适合高校馆开展学科服务。     

BLOG在企业知识管理中的应用

本文从什么是博客入手,分析了博客与以往网络形式(比如BBS和个人主页)的差别,尝试对博客在企业知识管理中的应用及其在知识管理中所起的作用进行初步探析。     

基于用户协作的非物质文化遗产数字资源分类模式研究

非物质文化遗产数据库对非遗资源的分类,必须遵从《非物质文化遗产数字化保护专业标准》,但这种分类方式存在一些问题。为了充分揭示非遗资源的特性和非遗资源之间的文化关联性,以建设承德地区非遗数据库为例,引入大众标注标引资源的方式来补充专家分类的不足：用户协作建设基础标签库,使用基础标签作为推荐标签,使用时间、空间、文化场所标签作为文化空间标签,由推荐标签等形成的高频标签作为专家分类的二级类目的备选,构建基于用户协作的非遗数字资源混合分类模式。     

创新资源集聚水平对高技术产业创新绩效影响的实证研究

随着知识经济的发展及技术创新的进步,人力、财力等创新资源成为各创新主体竞争的焦点。运用区位商方法测算了创新人力资源和创新财力资源的集聚水平,并将这两种集聚水平引入知识生产函数模型中,考察了创新资源集聚水平对创新绩效的影响及其非线性作用,对行业间的差异性进行了比较分析。研究发现,创新人力资源及财力资源集聚水平对创新绩效有非线性影响,创新人力资源与财力资源的交互作用对创新绩效有着显著的正向影响。     

博客在深化高校图书馆学科馆员工作中的作用

阐述了学科馆员工作的意义、起源和发展现状,针对目前学科馆员工作的不足从博客的特征出发,探讨了其在学科馆员工作中应用的可行性。进而,从提升学科馆员素质、丰富信息资源、虚拟用户学习几方面提出了利用博客深化学科馆员工作的建议。     

图书馆数字资源管理困境与创新

针对知识经济时代图书馆数字资源管理面临的挑战,从数字资源建设、数字资源安全两个方面探讨图书馆数字资源管理的困境,以其为图书馆数字资源管理创新提供依据,并从扩充自建数字资源的体量和科学管理数据两个方面提出基本路径,展望图书馆数字资源管理的未来发展方向。     

合作新产品开发知识资源动态投入决策研究

现有对合作新产品开发中资源投入决策的研究常常忽视知识资源的重要性和独特性,特别是未认识到企业间双向、多次的知识转移过程,以及此过程对企业知识资源投入的动态影响。本文以供应链上下游两个企业间的合作研发环节为例,基于知识开发和双向、多次的知识转移过程构建了合作开发模型,并在考虑知识水平增长滞后性的基础上,分别探讨了在不同的初始知识水平、滞后效应等情况下最优的知识资源投入决策,最后借助数值实验展现了相应的变化趋势。研究表明：在考虑双向、多次知识转移过程的情况下,最优资源投入决策在研发周期内动态改变,而合作双方的初始知识水平会明显影响整个过程中最优资源投入决策的变化趋势;在最优资源投入决策中,知识开发过程中资源投入量的最大值总是出现在期初时刻,而知识转移过程中资源投入量的最大值在不同情况下会有所变动     

基于知识元的文物图像资源细粒度知识表示方法研究

【目的/意义】文物图像资源日益成为数字人文基础设施建设的重要内容,为了克服存在于图像资源内容与 形式上的“语义鸿沟”对其开发利用产生的消极影响,有必要面向文物图像资源底层视觉特征与高层语义特征的精 细化映射与细粒度知识表示进行相关研究。【方法/过程】本文在分析文物图像资源知识表示需求与表示策略的基 础上,提出了基于知识元构造的文物图像资源细粒度知识表示模型。在模型设计的基础上,以著名绘画文物《历代 帝王图卷》为例,阐述了面向文物图像资源细粒度表示需求进行知识元提取、构造与数据发布的具体流程。【结果/ 结论】实验结果表明,本文提出的基于知识元的文物图像资源细粒度知识表示方法能够在图像底层视觉特征与高 层语义特征之间建立有效的语义映射关系,并通过与外部知识库的数据关联实现与开放关联数据网络的深度融 合。【创新/局限】本文从知识元角度出发,提出了文物图像资源的细粒度知识表示方法,在未来的研究中还需对文 物图像知识元的自动提取以及基于知识元的图像资源知识发现方法进行更深入地探索。     

学科服务中信息资源组织实践与思考

信息资源是学科服务的基础,借助网络信息技术合理组织信息资源,有助于提升学科服务质量,提高信息利用率。文章以西安交通大学学科服务中引入资源发现系统、建立学科博客服务平台为例,阐述了学科服务中如何借助信息技术手段组织信息资源,为学科用户提供个性化、特色化学科信息服务。     

语义网环境中的叙词表实例研究——利用SKOS构造机器可理解的知识组织体系

本文对叙词表在知识组织体系知识层面与语义网核心Ontology结合，阐述了叙词表表达知识概念与语义关系的能力为语义网建设提供资源组织基础；在描述层面利用SKOS对叙词表进行实例改造，对叙词语义关系可视化表示以及对网页进行主题标引。最后指出SKOS为知识组织体系提供一套简单，灵活，可扩展的机器可理解的描述和转化机制。     

网络嵌入、关系资源与知识获取机制

通过网络嵌入构建关系资源是网络条件下获取知识的重要机制。论文首先分析了网络嵌入条件下外部知识获取中的三大关系资源机制:溢出机制、共享机制和挖掘机制。在此基础上,论文构建了网络嵌入影响一国知识获取的关系资源综合效应模型,认为一个国家的核心企业对国外网络和国内网络的双边嵌入有利于提升该国知识水平,具体表现为两个方面,一方面通过关系资源作用机制实现的直接效应,另一方面通过影响吸收能力和研发投入实现的间接效应。最后通过建立结构方程模型进行了实证研究,发现与理论分析一致的结论。     

Sememe knowledge and auxiliary information enhanced approach for sarcasm detection

Sarcasm expression is a pervasive literary technique in which people intentionally express the opposite of what is implied. Accurate detection of sarcasm in a text can facilitate the understanding of speakers’ true intentions and promote other natural language processing tasks, especially sentiment analysis tasks. Since sarcasm is a kind of implicit sentiment expression and speakers deliberately confuse the audience, it is challenging to detect sarcasm only by text. Existing approaches based on machine learning and deep learning achieved unsatisfactory performance when handling sarcasm text with complex expression or needing specific background knowledge to understand. Especially, due to the characteristics of the Chinese language itself, sarcasm detection in Chinese is more difficult. To alleviate this dilemma on Chinese sarcasm detection, we propose a sememe and auxiliary enhanced attention neural model, SAAG. At the word level, we introduce sememe knowledge to enhance the representation learning of Chinese words. Sememe is the minimum unit of meaning, which is a fine-grained portrayal of a word. At the sentence level, we leverage some auxiliary information, such as the news title, to learning the representation of the context and background of sarcasm expression. Then, we construct the representation of text expression progressively and dynamically. The evaluation on a sarcasm dateset, consisting of comments on news text, reveals that our proposed approach is effective and outperforms the state-of-the-art models.     

组织沟通方式对沟通满意度的影响:沟通认知与沟通倾向的调节作用

随着知识经济时代的到来和推进,增进员工的沟通满意度成为提高组织人力资源管理水平的重要途径。以沟通认知和沟通倾向作为调节变量构建沟通方式对沟通满意度的影响模型。在对来自黑龙江23家企业373位员工调查数据研究的基础上,采用相关分析、回归分析等统计方法对影响模型进行检验。结果显示:在组织的纵向沟通中,正式沟通和非正式沟通方式都能够对沟通满意度产生正向效应,而正式沟通方式的效果更为明显;在这种正向关系中,沟通倾向表现出比沟通认知更显著的调节作用,且非正式沟通比正式沟通方式受到的调节作用更强烈。     

基于全文知识网络的学术资源关联发现实践

【目的/意义】通过对学术资源进行深度挖掘与语义化组织,实现学术资源及其内部知识之间的关联发现。 【方法/过程】本文提出基于全文知识网络的学术资源关联发现方法,设计了全文知识网络的模型和构建流程,以 Pubmed Central数据库中拟南芥（Arabidopsis）相关的520篇期刊论文全文数据为实验对象,通过全文解析和挖掘将 其分解为细粒度的知识,形成全文知识网络。然后利用SPARQL查询和RelFinder可视化工具从数字资源层、知识 单元层和知识对象层三个层次开展关联发现实验。【结果/结论】本文构建全文知识网络对学术资源进行细粒度组 织和挖掘,有助于发现不同学术资源及其内部知识之间的潜在关联,对学术资源的深度利用具有重要的意义。【创 新/局限】本文创新之处在于通过构建全文知识网络对学术资源进行细粒度揭示和组织并进一步发现潜在关联,局 限在于尚未开展大规模应用实践。